Overview

Dataset statistics

Number of variables29
Number of observations130
Missing cells170
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.6 KiB
Average record size in memory233.0 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-03" Constant
url has a high cardinality: 130 distinct values High cardinality
name has a high cardinality: 118 distinct values High cardinality
_embedded_show_url has a high cardinality: 86 distinct values High cardinality
_embedded_show_name has a high cardinality: 85 distinct values High cardinality
_embedded_show_premiered has a high cardinality: 65 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 76 distinct values High cardinality
_embedded_show_summary has a high cardinality: 72 distinct values High cardinality
_links_self_href has a high cardinality: 130 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
season is highly correlated with numberHigh correlation
number is highly correlated with seasonHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_name and 12 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_name and 5 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
summary is highly correlated with airdate and 1 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_name and 5 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
image is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
id is highly correlated with airtime and 13 other fieldsHigh correlation
season is highly correlated with number and 10 other fieldsHigh correlation
number is highly correlated with season and 11 other fieldsHigh correlation
type is highly correlated with runtime and 5 other fieldsHigh correlation
airtime is highly correlated with id and 15 other fieldsHigh correlation
airstamp is highly correlated with id and 12 other fieldsHigh correlation
runtime is highly correlated with season and 14 other fieldsHigh correlation
image is highly correlated with id and 20 other fieldsHigh correlation
summary is highly correlated with image and 3 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_type is highly correlated with season and 18 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 14 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_status is highly correlated with image and 13 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 14 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with season and 13 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 14 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 14 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with id and 6 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_updated is highly correlated with airstamp and 12 other fieldsHigh correlation
number has 3 (2.3%) missing values Missing
runtime has 17 (13.1%) missing values Missing
image has 99 (76.2%) missing values Missing
_embedded_show_runtime has 40 (30.8%) missing values Missing
_embedded_show_averageRuntime has 11 (8.5%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:00:20.640956
Analysis finished2022-05-10 02:00:59.018317
Duration38.38 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2003972.723
Minimum1944214
Maximum2289865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:00:59.093571image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1944214
5-th percentile1953909.6
Q11972802.5
median1979297.5
Q31999103.25
95-th percentile2173298.5
Maximum2289865
Range345651
Interquartile range (IQR)26300.75

Descriptive statistics

Standard deviation67600.26158
Coefficient of variation (CV)0.03373312461
Kurtosis6.431935491
Mean2003972.723
Median Absolute Deviation (MAD)9739
Skewness2.597218689
Sum260516454
Variance4569795366
MonotonicityNot monotonic
2022-05-09T21:00:59.273095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19798251
 
0.8%
19643911
 
0.8%
19738931
 
0.8%
19985281
 
0.8%
19652641
 
0.8%
22893761
 
0.8%
22898651
 
0.8%
21253441
 
0.8%
20718041
 
0.8%
20249081
 
0.8%
Other values (120)120
92.3%
ValueCountFrequency (%)
19442141
0.8%
19448821
0.8%
19477071
0.8%
19503651
0.8%
19506991
0.8%
19534641
0.8%
19534651
0.8%
19544531
0.8%
19589601
0.8%
19589611
0.8%
ValueCountFrequency (%)
22898651
0.8%
22893761
0.8%
22364911
0.8%
22059691
0.8%
22059681
0.8%
21895511
0.8%
21761201
0.8%
21698501
0.8%
21691991
0.8%
21539921
0.8%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/episodes/1979825/sim-for-you-4x17-chanyeols-episode-17
 
1
https://www.tvmaze.com/episodes/1964391/as-five-1x04-como-pode-um-peixe-vivo
 
1
https://www.tvmaze.com/episodes/1973893/sesame-street-51x04-bye-bye-boo-boos
 
1
https://www.tvmaze.com/episodes/1998528/mermaid-prince-1x14-episode-14
 
1
https://www.tvmaze.com/episodes/1965264/oh-mando-1x05-episode-5
 
1
Other values (125)
125 

Length

Max length139
Median length98.5
Mean length80.93076923
Min length55

Characters and Unicode

Total characters10521
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1979825/sim-for-you-4x17-chanyeols-episode-17
2nd rowhttps://www.tvmaze.com/episodes/1963996/257-pricin-ctoby-zit-2x06-seria-19
3rd rowhttps://www.tvmaze.com/episodes/1960726/psih-1x05-revnost
4th rowhttps://www.tvmaze.com/episodes/1954453/serlok-v-rossii-1x07-serdce-holmsa-i
5th rowhttps://www.tvmaze.com/episodes/1969558/neznost-1x10-seria-10

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979825/sim-for-you-4x17-chanyeols-episode-171
 
0.8%
https://www.tvmaze.com/episodes/1964391/as-five-1x04-como-pode-um-peixe-vivo1
 
0.8%
https://www.tvmaze.com/episodes/1973893/sesame-street-51x04-bye-bye-boo-boos1
 
0.8%
https://www.tvmaze.com/episodes/1998528/mermaid-prince-1x14-episode-141
 
0.8%
https://www.tvmaze.com/episodes/1965264/oh-mando-1x05-episode-51
 
0.8%
https://www.tvmaze.com/episodes/2289376/blippi-2020-12-03-blippi-visits-the-science-museum-for-children-educational-videos-for-kids1
 
0.8%
https://www.tvmaze.com/episodes/2289865/discover-destination-ua-2x13-kherson-region-ukraine-day-21
 
0.8%
https://www.tvmaze.com/episodes/2125344/jessis-showterview-2020-12-03-ep26-with-joon-park1
 
0.8%
https://www.tvmaze.com/episodes/2071804/al-saleet-akhbar-8x42-mlwn-abwk-ya-far1
 
0.8%
https://www.tvmaze.com/episodes/2024908/el-anesa-farah-2x15-episode-151
 
0.8%
Other values (120)120
92.3%

Length

2022-05-09T21:00:59.483853image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979825/sim-for-you-4x17-chanyeols-episode-171
 
0.8%
https://www.tvmaze.com/episodes/1979371/melon-music-awards-2020-12-03-day-21
 
0.8%
https://www.tvmaze.com/episodes/1954453/serlok-v-rossii-1x07-serdce-holmsa-i1
 
0.8%
https://www.tvmaze.com/episodes/1969558/neznost-1x10-seria-101
 
0.8%
https://www.tvmaze.com/episodes/1969559/neznost-1x11-seria-111
 
0.8%
https://www.tvmaze.com/episodes/1979224/kotiki-1x04-seria-41
 
0.8%
https://www.tvmaze.com/episodes/1971568/mermaid-prince-2x08-episode-81
 
0.8%
https://www.tvmaze.com/episodes/1985785/theres-a-pit-in-my-senior-martial-brothers-brain-2x07-episode-71
 
0.8%
https://www.tvmaze.com/episodes/1944214/quan-zhi-gao-shou-2x11-little-cold-hands1
 
0.8%
https://www.tvmaze.com/episodes/1972555/the-wolf-1x13-episode-131
 
0.8%
Other values (120)120
92.3%

Most occurring characters

ValueCountFrequency (%)
e869
 
8.3%
-793
 
7.5%
s686
 
6.5%
t674
 
6.4%
/650
 
6.2%
o589
 
5.6%
w449
 
4.3%
a437
 
4.2%
i387
 
3.7%
p368
 
3.5%
Other values (30)4619
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7242
68.8%
Decimal Number1446
 
13.7%
Other Punctuation1040
 
9.9%
Dash Punctuation793
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e869
12.0%
s686
 
9.5%
t674
 
9.3%
o589
 
8.1%
w449
 
6.2%
a437
 
6.0%
i387
 
5.3%
p368
 
5.1%
m356
 
4.9%
h286
 
3.9%
Other values (16)2141
29.6%
Decimal Number
ValueCountFrequency (%)
1340
23.5%
9183
12.7%
0171
11.8%
2167
11.5%
8112
 
7.7%
6100
 
6.9%
799
 
6.8%
598
 
6.8%
391
 
6.3%
485
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/650
62.5%
.260
 
25.0%
:130
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-793
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7242
68.8%
Common3279
31.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e869
12.0%
s686
 
9.5%
t674
 
9.3%
o589
 
8.1%
w449
 
6.2%
a437
 
6.0%
i387
 
5.3%
p368
 
5.1%
m356
 
4.9%
h286
 
3.9%
Other values (16)2141
29.6%
Common
ValueCountFrequency (%)
-793
24.2%
/650
19.8%
1340
10.4%
.260
 
7.9%
9183
 
5.6%
0171
 
5.2%
2167
 
5.1%
:130
 
4.0%
8112
 
3.4%
6100
 
3.0%
Other values (4)373
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII10521
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e869
 
8.3%
-793
 
7.5%
s686
 
6.5%
t674
 
6.4%
/650
 
6.2%
o589
 
5.6%
w449
 
4.3%
a437
 
4.2%
i387
 
3.7%
p368
 
3.5%
Other values (30)4619
43.9%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct118
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Episode 5
 
3
Episode 3
 
3
Episode 1
 
3
Episode 22
 
3
Episode 14
 
2
Other values (113)
116 

Length

Max length91
Median length48
Mean length17.86153846
Min length5

Characters and Unicode

Total characters2322
Distinct characters130
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)84.6%

Sample

1st rowChanyeol's Episode 17
2nd rowСерия 19
3rd rowРевность
4th rowСердце Холмса I
5th rowСерия 10

Common Values

ValueCountFrequency (%)
Episode 53
 
2.3%
Episode 33
 
2.3%
Episode 13
 
2.3%
Episode 223
 
2.3%
Episode 142
 
1.5%
Episode 152
 
1.5%
The Sanctuary2
 
1.5%
Episode 212
 
1.5%
Meet other guy at my birthday1
 
0.8%
ملعون أبوك يا فأر1
 
0.8%
Other values (108)108
83.1%

Length

2022-05-09T21:00:59.681239image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode34
 
8.5%
the15
 
3.7%
5
 
1.2%
34
 
1.0%
серия4
 
1.0%
a4
 
1.0%
173
 
0.7%
23
 
0.7%
53
 
0.7%
13
 
0.7%
Other values (301)324
80.6%

Most occurring characters

ValueCountFrequency (%)
272
 
11.7%
e194
 
8.4%
o131
 
5.6%
i124
 
5.3%
a111
 
4.8%
s101
 
4.3%
n78
 
3.4%
r77
 
3.3%
t75
 
3.2%
d74
 
3.2%
Other values (120)1085
46.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1569
67.6%
Uppercase Letter335
 
14.4%
Space Separator272
 
11.7%
Decimal Number87
 
3.7%
Other Punctuation24
 
1.0%
Other Letter23
 
1.0%
Close Punctuation4
 
0.2%
Open Punctuation4
 
0.2%
Math Symbol2
 
0.1%
Modifier Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e194
 
12.4%
o131
 
8.3%
i124
 
7.9%
a111
 
7.1%
s101
 
6.4%
n78
 
5.0%
r77
 
4.9%
t75
 
4.8%
d74
 
4.7%
l61
 
3.9%
Other values (46)543
34.6%
Uppercase Letter
ValueCountFrequency (%)
E56
16.7%
T25
 
7.5%
S22
 
6.6%
B19
 
5.7%
P18
 
5.4%
H16
 
4.8%
L16
 
4.8%
A15
 
4.5%
R15
 
4.5%
C14
 
4.2%
Other values (24)119
35.5%
Other Letter
ValueCountFrequency (%)
ل3
13.0%
ا3
13.0%
ق2
 
8.7%
م2
 
8.7%
و2
 
8.7%
أ2
 
8.7%
ع1
 
4.3%
ن1
 
4.3%
ب1
 
4.3%
ك1
 
4.3%
Other values (5)5
21.7%
Decimal Number
ValueCountFrequency (%)
126
29.9%
218
20.7%
48
 
9.2%
57
 
8.0%
37
 
8.0%
76
 
6.9%
06
 
6.9%
64
 
4.6%
93
 
3.4%
82
 
2.3%
Other Punctuation
ValueCountFrequency (%)
'6
25.0%
,5
20.8%
&3
12.5%
:2
 
8.3%
!2
 
8.3%
?2
 
8.3%
"2
 
8.3%
.1
 
4.2%
#1
 
4.2%
Space Separator
ValueCountFrequency (%)
272
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Modifier Symbol
ValueCountFrequency (%)
`1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1719
74.0%
Common395
 
17.0%
Cyrillic185
 
8.0%
Arabic23
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e194
 
11.3%
o131
 
7.6%
i124
 
7.2%
a111
 
6.5%
s101
 
5.9%
n78
 
4.5%
r77
 
4.5%
t75
 
4.4%
d74
 
4.3%
l61
 
3.5%
Other values (46)693
40.3%
Cyrillic
ValueCountFrequency (%)
о17
 
9.2%
а17
 
9.2%
р17
 
9.2%
е16
 
8.6%
т16
 
8.6%
и14
 
7.6%
д8
 
4.3%
н8
 
4.3%
с8
 
4.3%
в7
 
3.8%
Other values (24)57
30.8%
Common
ValueCountFrequency (%)
272
68.9%
126
 
6.6%
218
 
4.6%
48
 
2.0%
57
 
1.8%
37
 
1.8%
'6
 
1.5%
76
 
1.5%
06
 
1.5%
,5
 
1.3%
Other values (15)34
 
8.6%
Arabic
ValueCountFrequency (%)
ل3
13.0%
ا3
13.0%
ق2
 
8.7%
م2
 
8.7%
و2
 
8.7%
أ2
 
8.7%
ع1
 
4.3%
ن1
 
4.3%
ب1
 
4.3%
ك1
 
4.3%
Other values (5)5
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2098
90.4%
Cyrillic185
 
8.0%
Arabic23
 
1.0%
None16
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
272
 
13.0%
e194
 
9.2%
o131
 
6.2%
i124
 
5.9%
a111
 
5.3%
s101
 
4.8%
n78
 
3.7%
r77
 
3.7%
t75
 
3.6%
d74
 
3.5%
Other values (65)861
41.0%
Cyrillic
ValueCountFrequency (%)
о17
 
9.2%
а17
 
9.2%
р17
 
9.2%
е16
 
8.6%
т16
 
8.6%
и14
 
7.6%
д8
 
4.3%
н8
 
4.3%
с8
 
4.3%
в7
 
3.8%
Other values (24)57
30.8%
None
ValueCountFrequency (%)
ł5
31.2%
ę4
25.0%
ø3
18.8%
ś2
 
12.5%
ń1
 
6.2%
ż1
 
6.2%
Arabic
ValueCountFrequency (%)
ل3
13.0%
ا3
13.0%
ق2
 
8.7%
م2
 
8.7%
و2
 
8.7%
أ2
 
8.7%
ع1
 
4.3%
ن1
 
4.3%
ب1
 
4.3%
ك1
 
4.3%
Other values (5)5
21.7%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.2461538
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:00:59.836020image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation486.6130542
Coefficient of variation (CV)3.82418674
Kurtosis11.80430336
Mean127.2461538
Median Absolute Deviation (MAD)0
Skewness3.690416771
Sum16542
Variance236792.2645
MonotonicityNot monotonic
2022-05-09T21:00:59.970278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
189
68.5%
211
 
8.5%
20208
 
6.2%
45
 
3.8%
83
 
2.3%
33
 
2.3%
52
 
1.5%
101
 
0.8%
541
 
0.8%
131
 
0.8%
Other values (6)6
 
4.6%
ValueCountFrequency (%)
189
68.5%
211
 
8.5%
33
 
2.3%
45
 
3.8%
52
 
1.5%
71
 
0.8%
83
 
2.3%
91
 
0.8%
101
 
0.8%
131
 
0.8%
ValueCountFrequency (%)
20208
6.2%
541
 
0.8%
511
 
0.8%
311
 
0.8%
181
 
0.8%
151
 
0.8%
131
 
0.8%
101
 
0.8%
91
 
0.8%
83
 
2.3%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct45
Distinct (%)35.4%
Missing3
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean21.81102362
Minimum1
Maximum330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:00.154284image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q14
median8
Q321.5
95-th percentile74.8
Maximum330
Range329
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation43.42841808
Coefficient of variation (CV)1.991122417
Kurtosis30.93755623
Mean21.81102362
Median Absolute Deviation (MAD)5
Skewness5.133349789
Sum2770
Variance1886.027497
MonotonicityNot monotonic
2022-05-09T21:01:00.295932image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
414
 
10.8%
510
 
7.7%
88
 
6.2%
37
 
5.4%
17
 
5.4%
77
 
5.4%
27
 
5.4%
106
 
4.6%
115
 
3.8%
65
 
3.8%
Other values (35)51
39.2%
ValueCountFrequency (%)
17
5.4%
27
5.4%
37
5.4%
414
10.8%
510
7.7%
65
 
3.8%
77
5.4%
88
6.2%
91
 
0.8%
106
4.6%
ValueCountFrequency (%)
3301
0.8%
2891
0.8%
1441
0.8%
1181
0.8%
1071
0.8%
951
0.8%
821
0.8%
581
0.8%
561
0.8%
521
0.8%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
regular
127 
insignificant_special
 
3

Length

Max length21
Median length7
Mean length7.323076923
Min length7

Characters and Unicode

Total characters952
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular127
97.7%
insignificant_special3
 
2.3%

Length

2022-05-09T21:01:00.405303image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:01:00.508516image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular127
97.7%
insignificant_special3
 
2.3%

Most occurring characters

ValueCountFrequency (%)
r254
26.7%
a133
14.0%
e130
13.7%
g130
13.7%
l130
13.7%
u127
13.3%
i15
 
1.6%
n9
 
0.9%
s6
 
0.6%
c6
 
0.6%
Other values (4)12
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter949
99.7%
Connector Punctuation3
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r254
26.8%
a133
14.0%
e130
13.7%
g130
13.7%
l130
13.7%
u127
13.4%
i15
 
1.6%
n9
 
0.9%
s6
 
0.6%
c6
 
0.6%
Other values (3)9
 
0.9%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin949
99.7%
Common3
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r254
26.8%
a133
14.0%
e130
13.7%
g130
13.7%
l130
13.7%
u127
13.4%
i15
 
1.6%
n9
 
0.9%
s6
 
0.6%
c6
 
0.6%
Other values (3)9
 
0.9%
Common
ValueCountFrequency (%)
_3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r254
26.7%
a133
14.0%
e130
13.7%
g130
13.7%
l130
13.7%
u127
13.3%
i15
 
1.6%
n9
 
0.9%
s6
 
0.6%
c6
 
0.6%
Other values (4)12
 
1.3%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-03
130 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1300
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-03
2nd row2020-12-03
3rd row2020-12-03
4th row2020-12-03
5th row2020-12-03

Common Values

ValueCountFrequency (%)
2020-12-03130
100.0%

Length

2022-05-09T21:01:00.602905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:01:00.707437image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-03130
100.0%

Most occurring characters

ValueCountFrequency (%)
2390
30.0%
0390
30.0%
-260
20.0%
1130
 
10.0%
3130
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1040
80.0%
Dash Punctuation260
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2390
37.5%
0390
37.5%
1130
 
12.5%
3130
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-260
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2390
30.0%
0390
30.0%
-260
20.0%
1130
 
10.0%
3130
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2390
30.0%
0390
30.0%
-260
20.0%
1130
 
10.0%
3130
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct14
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
94 
20:00
13 
06:00
 
5
12:00
 
4
21:00
 
3
Other values (9)
11 

Length

Max length5
Median length3
Mean length3.553846154
Min length3

Characters and Unicode

Total characters462
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)5.4%

Sample

1st row06:00
2nd rownan
3rd row12:00
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan94
72.3%
20:0013
 
10.0%
06:005
 
3.8%
12:004
 
3.1%
21:003
 
2.3%
11:002
 
1.5%
18:002
 
1.5%
17:351
 
0.8%
17:001
 
0.8%
20:201
 
0.8%
Other values (4)4
 
3.1%

Length

2022-05-09T21:01:00.792243image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan94
72.3%
20:0013
 
10.0%
06:005
 
3.8%
12:004
 
3.1%
21:003
 
2.3%
11:002
 
1.5%
18:002
 
1.5%
17:351
 
0.8%
17:001
 
0.8%
20:201
 
0.8%
Other values (4)4
 
3.1%

Most occurring characters

ValueCountFrequency (%)
n188
40.7%
a94
20.3%
088
19.0%
:36
 
7.8%
223
 
5.0%
118
 
3.9%
65
 
1.1%
53
 
0.6%
82
 
0.4%
72
 
0.4%
Other values (2)3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter282
61.0%
Decimal Number144
31.2%
Other Punctuation36
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
088
61.1%
223
 
16.0%
118
 
12.5%
65
 
3.5%
53
 
2.1%
82
 
1.4%
72
 
1.4%
92
 
1.4%
31
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
n188
66.7%
a94
33.3%
Other Punctuation
ValueCountFrequency (%)
:36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin282
61.0%
Common180
39.0%

Most frequent character per script

Common
ValueCountFrequency (%)
088
48.9%
:36
20.0%
223
 
12.8%
118
 
10.0%
65
 
2.8%
53
 
1.7%
82
 
1.1%
72
 
1.1%
92
 
1.1%
31
 
0.6%
Latin
ValueCountFrequency (%)
n188
66.7%
a94
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII462
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n188
40.7%
a94
20.3%
088
19.0%
:36
 
7.8%
223
 
5.0%
118
 
3.9%
65
 
1.1%
53
 
0.6%
82
 
0.4%
72
 
0.4%
Other values (2)3
 
0.6%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct22
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-03T12:00:00+00:00
49 
2020-12-03T17:00:00+00:00
28 
2020-12-03T04:00:00+00:00
11 
2020-12-03T11:00:00+00:00
2020-12-03T00:00:00+00:00
Other values (17)
28 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters3250
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)8.5%

Sample

1st row2020-12-02T21:00:00+00:00
2nd row2020-12-03T00:00:00+00:00
3rd row2020-12-03T00:00:00+00:00
4th row2020-12-03T00:00:00+00:00
5th row2020-12-03T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-03T12:00:00+00:0049
37.7%
2020-12-03T17:00:00+00:0028
21.5%
2020-12-03T04:00:00+00:0011
 
8.5%
2020-12-03T11:00:00+00:008
 
6.2%
2020-12-03T00:00:00+00:006
 
4.6%
2020-12-03T09:00:00+00:004
 
3.1%
2020-12-03T05:00:00+00:004
 
3.1%
2020-12-03T14:00:00+00:003
 
2.3%
2020-12-03T08:00:00+00:002
 
1.5%
2020-12-03T13:00:00+00:002
 
1.5%
Other values (12)13
 
10.0%

Length

2022-05-09T21:01:00.904349image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-03t12:00:00+00:0049
37.7%
2020-12-03t17:00:00+00:0028
21.5%
2020-12-03t04:00:00+00:0011
 
8.5%
2020-12-03t11:00:00+00:008
 
6.2%
2020-12-03t00:00:00+00:006
 
4.6%
2020-12-03t09:00:00+00:004
 
3.1%
2020-12-03t05:00:00+00:004
 
3.1%
2020-12-03t14:00:00+00:003
 
2.3%
2020-12-03t08:00:00+00:002
 
1.5%
2020-12-03t13:00:00+00:002
 
1.5%
Other values (12)13
 
10.0%

Most occurring characters

ValueCountFrequency (%)
01467
45.1%
2445
 
13.7%
:390
 
12.0%
-260
 
8.0%
1234
 
7.2%
3133
 
4.1%
T130
 
4.0%
+130
 
4.0%
729
 
0.9%
414
 
0.4%
Other values (4)18
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2340
72.0%
Other Punctuation390
 
12.0%
Dash Punctuation260
 
8.0%
Uppercase Letter130
 
4.0%
Math Symbol130
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01467
62.7%
2445
 
19.0%
1234
 
10.0%
3133
 
5.7%
729
 
1.2%
414
 
0.6%
58
 
0.3%
95
 
0.2%
84
 
0.2%
61
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
:390
100.0%
Dash Punctuation
ValueCountFrequency (%)
-260
100.0%
Uppercase Letter
ValueCountFrequency (%)
T130
100.0%
Math Symbol
ValueCountFrequency (%)
+130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3120
96.0%
Latin130
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01467
47.0%
2445
 
14.3%
:390
 
12.5%
-260
 
8.3%
1234
 
7.5%
3133
 
4.3%
+130
 
4.2%
729
 
0.9%
414
 
0.4%
58
 
0.3%
Other values (3)10
 
0.3%
Latin
ValueCountFrequency (%)
T130
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01467
45.1%
2445
 
13.7%
:390
 
12.0%
-260
 
8.0%
1234
 
7.2%
3133
 
4.1%
T130
 
4.0%
+130
 
4.0%
729
 
0.9%
414
 
0.4%
Other values (4)18
 
0.6%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)38.1%
Missing17
Missing (%)13.1%
Infinite0
Infinite (%)0.0%
Mean36.78761062
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:01.135914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10.6
Q114
median30
Q345
95-th percentile60
Maximum300
Range298
Interquartile range (IQR)31

Descriptive statistics

Standard deviation38.07217097
Coefficient of variation (CV)1.034918287
Kurtosis26.8935146
Mean36.78761062
Median Absolute Deviation (MAD)15
Skewness4.580438795
Sum4157
Variance1449.490202
MonotonicityNot monotonic
2022-05-09T21:01:01.271796image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4521
16.2%
1111
 
8.5%
208
 
6.2%
127
 
5.4%
307
 
5.4%
606
 
4.6%
134
 
3.1%
523
 
2.3%
253
 
2.3%
213
 
2.3%
Other values (33)40
30.8%
(Missing)17
13.1%
ValueCountFrequency (%)
21
 
0.8%
41
 
0.8%
71
 
0.8%
81
 
0.8%
91
 
0.8%
101
 
0.8%
1111
8.5%
127
5.4%
134
 
3.1%
141
 
0.8%
ValueCountFrequency (%)
3001
 
0.8%
2401
 
0.8%
1401
 
0.8%
1201
 
0.8%
661
 
0.8%
606
4.6%
561
 
0.8%
531
 
0.8%
523
2.3%
502
 
1.5%

image
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct31
Distinct (%)100.0%
Missing99
Missing (%)76.2%
Memory size1.1 KiB
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752690.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752690.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732255.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732255.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/363/908139.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/363/908139.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726709.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726709.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/731762.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/731762.jpg'}
 
1
Other values (26)
26 

Length

Max length178
Median length176
Mean length176.0645161
Min length176

Characters and Unicode

Total characters5458
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752690.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752690.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/312/781439.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/312/781439.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/312/781441.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/312/781441.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/286/716106.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/286/716106.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/277/694629.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/277/694629.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752690.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752690.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732255.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732255.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/363/908139.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/363/908139.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726709.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726709.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/731762.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/731762.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723344.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723344.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723350.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723350.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723349.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723349.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/327/818567.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/327/818567.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/327/818566.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/327/818566.jpg'}1
 
0.8%
Other values (21)21
 
16.2%
(Missing)99
76.2%

Length

2022-05-09T21:01:01.391028image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium31
25.0%
original31
25.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720609.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/716044.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/390/977053.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/390/977053.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/390/977052.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/390/977052.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716053.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/716053.jpg1
 
0.8%
Other values (54)54
43.5%

Most occurring characters

ValueCountFrequency (%)
/434
 
8.0%
a372
 
6.8%
t341
 
6.2%
m310
 
5.7%
i310
 
5.7%
s279
 
5.1%
e248
 
4.5%
'248
 
4.5%
o217
 
4.0%
p217
 
4.0%
Other values (28)2482
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3658
67.0%
Other Punctuation1023
 
18.7%
Decimal Number560
 
10.3%
Space Separator93
 
1.7%
Connector Punctuation62
 
1.1%
Close Punctuation31
 
0.6%
Open Punctuation31
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a372
 
10.2%
t341
 
9.3%
m310
 
8.5%
i310
 
8.5%
s279
 
7.6%
e248
 
6.8%
o217
 
5.9%
p217
 
5.9%
g186
 
5.1%
c186
 
5.1%
Other values (9)992
27.1%
Decimal Number
ValueCountFrequency (%)
290
16.1%
788
15.7%
158
10.4%
356
10.0%
656
10.0%
956
10.0%
852
9.3%
042
7.5%
432
 
5.7%
530
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/434
42.4%
'248
24.2%
.186
18.2%
:124
 
12.1%
,31
 
3.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Connector Punctuation
ValueCountFrequency (%)
_62
100.0%
Close Punctuation
ValueCountFrequency (%)
}31
100.0%
Open Punctuation
ValueCountFrequency (%)
{31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3658
67.0%
Common1800
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/434
24.1%
'248
13.8%
.186
10.3%
:124
 
6.9%
93
 
5.2%
290
 
5.0%
788
 
4.9%
_62
 
3.4%
158
 
3.2%
356
 
3.1%
Other values (9)361
20.1%
Latin
ValueCountFrequency (%)
a372
 
10.2%
t341
 
9.3%
m310
 
8.5%
i310
 
8.5%
s279
 
7.6%
e248
 
6.8%
o217
 
5.9%
p217
 
5.9%
g186
 
5.1%
c186
 
5.1%
Other values (9)992
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/434
 
8.0%
a372
 
6.8%
t341
 
6.2%
m310
 
5.7%
i310
 
5.7%
s279
 
5.1%
e248
 
4.5%
'248
 
4.5%
o217
 
4.0%
p217
 
4.0%
Other values (28)2482
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct47
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
84 
<p>When a ruthless demon with the ability to inhabit the body of any living being comes to Earth, not even Boner is safe.</p>
 
1
<p>When a gallery coordinator named Lama is stuck in an inescapable hole with Ali the artist, they push each other to confront the dark side of their lives.</p>
 
1
<p>Krisha joins the rest of the theater group in staging an LGBTQIA+ rally for their theater adviser, Mr. Siwa. Amidst the chaos of preparations, Vince and Leslie uncover Barry and Mando's secret.</p>
 
1
<p>Keyla auditions for a musical show. Benê starts giving piano lessons to Nem. Lica gets a freelancer. Tina moves into Lica's house.</p>
 
1
Other values (42)
42 

Length

Max length396
Median length3
Mean length69.30769231
Min length3

Characters and Unicode

Total characters9010
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)35.4%

Sample

1st row<p><b>#A refreshing break #I refuse any rewards #Going with the flow</b></p>
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan84
64.6%
<p>When a ruthless demon with the ability to inhabit the body of any living being comes to Earth, not even Boner is safe.</p>1
 
0.8%
<p>When a gallery coordinator named Lama is stuck in an inescapable hole with Ali the artist, they push each other to confront the dark side of their lives.</p>1
 
0.8%
<p>Krisha joins the rest of the theater group in staging an LGBTQIA+ rally for their theater adviser, Mr. Siwa. Amidst the chaos of preparations, Vince and Leslie uncover Barry and Mando's secret.</p>1
 
0.8%
<p>Keyla auditions for a musical show. Benê starts giving piano lessons to Nem. Lica gets a freelancer. Tina moves into Lica's house.</p>1
 
0.8%
<p>This week, host Wil Wheaton (Star Trek: The Next Generation) is joined by new stars Blu del Barrio (Adira) and Ian Alexander (Gray). The two young actors describe what it's like to join the massive Star Trek family, the impact of playing trans and non-binary characters, and just how hard it is to fake playing the cello.</p>1
 
0.8%
<p>The final four tackle themed tablescapes before a team challenge that celebrates the LGBTQIA+ community with brilliant floral barges.</p>1
 
0.8%
<p>The final florists create celebratory signature bouquets before transforming empty rooms into vibrant, flower-filled spaces that tell a story stunning enough to snag the life-changing $100,000 grand prize.</p>1
 
0.8%
<p>Before Chad, Faith, and Garrett can wine and dine a mystery suitor for their eighth date of Christmas, Garrett receives a sweet surprise. Later, when someone from Faith's past reenters the picture, what's to become of her future with Anthony? Meanwhile, the arrival of a gregarious new housemate puts the others on edge.</p>1
 
0.8%
<p>With only two dates remaining before our Leads must choose someone to take home, newcomer Chelsea makes up for lost time by commanding control of the festivities—and everyone's attention. After being prematurely friend-zoned by Dominick, Garrett hopes that some one-on-one time will reignite their spark.</p>1
 
0.8%
Other values (37)37
28.5%

Length

2022-05-09T21:01:01.525243image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan84
 
5.6%
the68
 
4.5%
to52
 
3.5%
a42
 
2.8%
and39
 
2.6%
of27
 
1.8%
with20
 
1.3%
p15
 
1.0%
for14
 
0.9%
her14
 
0.9%
Other values (763)1125
75.0%

Most occurring characters

ValueCountFrequency (%)
1356
15.0%
e809
 
9.0%
n661
 
7.3%
a630
 
7.0%
t575
 
6.4%
o506
 
5.6%
i488
 
5.4%
r438
 
4.9%
s437
 
4.9%
h331
 
3.7%
Other values (66)2779
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6831
75.8%
Space Separator1373
 
15.2%
Math Symbol262
 
2.9%
Other Punctuation257
 
2.9%
Uppercase Letter247
 
2.7%
Dash Punctuation25
 
0.3%
Decimal Number8
 
0.1%
Open Punctuation3
 
< 0.1%
Close Punctuation3
 
< 0.1%
Currency Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e809
11.8%
n661
 
9.7%
a630
 
9.2%
t575
 
8.4%
o506
 
7.4%
i488
 
7.1%
r438
 
6.4%
s437
 
6.4%
h331
 
4.8%
l271
 
4.0%
Other values (17)1685
24.7%
Uppercase Letter
ValueCountFrequency (%)
A31
12.6%
B30
12.1%
J19
 
7.7%
T19
 
7.7%
L15
 
6.1%
M13
 
5.3%
S13
 
5.3%
W12
 
4.9%
F11
 
4.5%
C11
 
4.5%
Other values (15)73
29.6%
Other Punctuation
ValueCountFrequency (%)
.78
30.4%
/72
28.0%
,63
24.5%
'30
 
11.7%
?4
 
1.6%
#3
 
1.2%
"2
 
0.8%
;2
 
0.8%
!1
 
0.4%
&1
 
0.4%
Math Symbol
ValueCountFrequency (%)
<130
49.6%
>130
49.6%
+2
 
0.8%
Decimal Number
ValueCountFrequency (%)
05
62.5%
12
 
25.0%
31
 
12.5%
Space Separator
ValueCountFrequency (%)
1356
98.8%
 17
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-18
72.0%
7
 
28.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7078
78.6%
Common1932
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e809
11.4%
n661
 
9.3%
a630
 
8.9%
t575
 
8.1%
o506
 
7.1%
i488
 
6.9%
r438
 
6.2%
s437
 
6.2%
h331
 
4.7%
l271
 
3.8%
Other values (42)1932
27.3%
Common
ValueCountFrequency (%)
1356
70.2%
<130
 
6.7%
>130
 
6.7%
.78
 
4.0%
/72
 
3.7%
,63
 
3.3%
'30
 
1.6%
-18
 
0.9%
 17
 
0.9%
7
 
0.4%
Other values (14)31
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII8985
99.7%
None18
 
0.2%
Punctuation7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1356
15.1%
e809
 
9.0%
n661
 
7.4%
a630
 
7.0%
t575
 
6.4%
o506
 
5.6%
i488
 
5.4%
r438
 
4.9%
s437
 
4.9%
h331
 
3.7%
Other values (63)2754
30.7%
None
ValueCountFrequency (%)
 17
94.4%
ê1
 
5.6%
Punctuation
ValueCountFrequency (%)
7
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct86
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46650.32308
Minimum2504
Maximum60848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:01.655090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile16884.85
Q144107.25
median51793.5
Q352548
95-th percentile56446.6
Maximum60848
Range58344
Interquartile range (IQR)8440.75

Descriptive statistics

Standard deviation11362.85902
Coefficient of variation (CV)0.2435751411
Kurtosis4.812401982
Mean46650.32308
Median Absolute Deviation (MAD)1590.5
Skewness-2.210210896
Sum6064542
Variance129114565.2
MonotonicityNot monotonic
2022-05-09T21:01:01.757762image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5254813
 
10.0%
518458
 
6.2%
428245
 
3.8%
521054
 
3.1%
520714
 
3.1%
454703
 
2.3%
586892
 
1.5%
527582
 
1.5%
524212
 
1.5%
521082
 
1.5%
Other values (76)85
65.4%
ValueCountFrequency (%)
25041
0.8%
61411
0.8%
65441
0.8%
74801
0.8%
132151
0.8%
152501
0.8%
167531
0.8%
170461
0.8%
248371
0.8%
262681
0.8%
ValueCountFrequency (%)
608481
0.8%
608091
0.8%
586892
1.5%
575561
0.8%
572571
0.8%
566051
0.8%
562531
0.8%
547441
0.8%
546581
0.8%
546101
0.8%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct86
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/shows/52548/bogdan-boner-egzorcysta
13 
https://www.tvmaze.com/shows/51845/stylish-with-jenna-lyons
 
8
https://www.tvmaze.com/shows/42824/looney-tunes-cartoons
 
5
https://www.tvmaze.com/shows/52105/be-with-you
 
4
https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cults
 
4
Other values (81)
96 

Length

Max length83
Median length62
Mean length51.80769231
Min length39

Characters and Unicode

Total characters6735
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)51.5%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit
3rd rowhttps://www.tvmaze.com/shows/49280/psih
4th rowhttps://www.tvmaze.com/shows/49422/serlok-v-rossii
5th rowhttps://www.tvmaze.com/shows/51908/neznost

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52548/bogdan-boner-egzorcysta13
 
10.0%
https://www.tvmaze.com/shows/51845/stylish-with-jenna-lyons8
 
6.2%
https://www.tvmaze.com/shows/42824/looney-tunes-cartoons5
 
3.8%
https://www.tvmaze.com/shows/52105/be-with-you4
 
3.1%
https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cults4
 
3.1%
https://www.tvmaze.com/shows/45470/12-dates-of-christmas3
 
2.3%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
1.5%
https://www.tvmaze.com/shows/52758/stichtag2
 
1.5%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
1.5%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
1.5%
Other values (76)85
65.4%

Length

2022-05-09T21:01:01.882462image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52548/bogdan-boner-egzorcysta13
 
10.0%
https://www.tvmaze.com/shows/51845/stylish-with-jenna-lyons8
 
6.2%
https://www.tvmaze.com/shows/42824/looney-tunes-cartoons5
 
3.8%
https://www.tvmaze.com/shows/52105/be-with-you4
 
3.1%
https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cults4
 
3.1%
https://www.tvmaze.com/shows/45470/12-dates-of-christmas3
 
2.3%
https://www.tvmaze.com/shows/53177/masrah-masr2
 
1.5%
https://www.tvmaze.com/shows/42843/the-flight-attendant2
 
1.5%
https://www.tvmaze.com/shows/51560/begin-again2
 
1.5%
https://www.tvmaze.com/shows/47912/the-wolf2
 
1.5%
Other values (76)85
65.4%

Most occurring characters

ValueCountFrequency (%)
/650
 
9.7%
t557
 
8.3%
w551
 
8.2%
s543
 
8.1%
o433
 
6.4%
h342
 
5.1%
e335
 
5.0%
m308
 
4.6%
a280
 
4.2%
.260
 
3.9%
Other values (30)2476
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4786
71.1%
Other Punctuation1040
 
15.4%
Decimal Number661
 
9.8%
Dash Punctuation248
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t557
11.6%
w551
11.5%
s543
11.3%
o433
 
9.0%
h342
 
7.1%
e335
 
7.0%
m308
 
6.4%
a280
 
5.9%
c193
 
4.0%
p159
 
3.3%
Other values (16)1085
22.7%
Decimal Number
ValueCountFrequency (%)
5129
19.5%
495
14.4%
283
12.6%
872
10.9%
170
10.6%
056
8.5%
643
 
6.5%
740
 
6.1%
937
 
5.6%
336
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/650
62.5%
.260
 
25.0%
:130
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4786
71.1%
Common1949
28.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t557
11.6%
w551
11.5%
s543
11.3%
o433
 
9.0%
h342
 
7.1%
e335
 
7.0%
m308
 
6.4%
a280
 
5.9%
c193
 
4.0%
p159
 
3.3%
Other values (16)1085
22.7%
Common
ValueCountFrequency (%)
/650
33.4%
.260
 
13.3%
-248
 
12.7%
:130
 
6.7%
5129
 
6.6%
495
 
4.9%
283
 
4.3%
872
 
3.7%
170
 
3.6%
056
 
2.9%
Other values (4)156
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6735
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/650
 
9.7%
t557
 
8.3%
w551
 
8.2%
s543
 
8.1%
o433
 
6.4%
h342
 
5.1%
e335
 
5.0%
m308
 
4.6%
a280
 
4.2%
.260
 
3.9%
Other values (30)2476
36.8%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct85
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Bogdan Boner: Egzorcysta
13 
Stylish with Jenna Lyons
 
8
Looney Tunes Cartoons
 
5
Heaven's Gate: The Cult of Cults
 
4
Be With You
 
4
Other values (80)
96 

Length

Max length50
Median length28
Mean length17.25384615
Min length4

Characters and Unicode

Total characters2243
Distinct characters103
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)50.0%

Sample

1st rowSim for You
2nd row257 причин, чтобы жить
3rd rowПсих
4th rowШерлок в России
5th rowНежность

Common Values

ValueCountFrequency (%)
Bogdan Boner: Egzorcysta13
 
10.0%
Stylish with Jenna Lyons8
 
6.2%
Looney Tunes Cartoons5
 
3.8%
Heaven's Gate: The Cult of Cults4
 
3.1%
Be With You4
 
3.1%
12 Dates of Christmas3
 
2.3%
Stichtag2
 
1.5%
You Complete Me2
 
1.5%
Psych Hunter2
 
1.5%
Full Bloom2
 
1.5%
Other values (75)85
65.4%

Length

2022-05-09T21:01:02.006306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the15
 
4.0%
bogdan13
 
3.4%
egzorcysta13
 
3.4%
boner13
 
3.4%
with12
 
3.2%
of9
 
2.4%
stylish8
 
2.1%
jenna8
 
2.1%
lyons8
 
2.1%
you8
 
2.1%
Other values (200)272
71.8%

Most occurring characters

ValueCountFrequency (%)
249
 
11.1%
e177
 
7.9%
o153
 
6.8%
n134
 
6.0%
a130
 
5.8%
t123
 
5.5%
s108
 
4.8%
r102
 
4.5%
i88
 
3.9%
h71
 
3.2%
Other values (93)908
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1578
70.4%
Uppercase Letter351
 
15.6%
Space Separator249
 
11.1%
Other Punctuation49
 
2.2%
Decimal Number15
 
0.7%
Dash Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e177
11.2%
o153
 
9.7%
n134
 
8.5%
a130
 
8.2%
t123
 
7.8%
s108
 
6.8%
r102
 
6.5%
i88
 
5.6%
h71
 
4.5%
l61
 
3.9%
Other values (42)431
27.3%
Uppercase Letter
ValueCountFrequency (%)
B46
13.1%
T36
 
10.3%
S34
 
9.7%
C25
 
7.1%
M22
 
6.3%
L20
 
5.7%
E18
 
5.1%
W15
 
4.3%
J14
 
4.0%
A13
 
3.7%
Other values (25)108
30.8%
Other Punctuation
ValueCountFrequency (%)
:21
42.9%
'11
22.4%
.6
 
12.2%
,4
 
8.2%
!3
 
6.1%
&2
 
4.1%
#1
 
2.0%
?1
 
2.0%
Decimal Number
ValueCountFrequency (%)
27
46.7%
13
20.0%
02
 
13.3%
71
 
6.7%
51
 
6.7%
61
 
6.7%
Space Separator
ValueCountFrequency (%)
249
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1823
81.3%
Common314
 
14.0%
Cyrillic106
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e177
 
9.7%
o153
 
8.4%
n134
 
7.4%
a130
 
7.1%
t123
 
6.7%
s108
 
5.9%
r102
 
5.6%
i88
 
4.8%
h71
 
3.9%
l61
 
3.3%
Other values (42)676
37.1%
Cyrillic
ValueCountFrequency (%)
и10
 
9.4%
о10
 
9.4%
е9
 
8.5%
т8
 
7.5%
н7
 
6.6%
к5
 
4.7%
с5
 
4.7%
а4
 
3.8%
С4
 
3.8%
ж3
 
2.8%
Other values (25)41
38.7%
Common
ValueCountFrequency (%)
249
79.3%
:21
 
6.7%
'11
 
3.5%
27
 
2.2%
.6
 
1.9%
,4
 
1.3%
!3
 
1.0%
13
 
1.0%
02
 
0.6%
&2
 
0.6%
Other values (6)6
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2134
95.1%
Cyrillic106
 
4.7%
None3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
 
11.7%
e177
 
8.3%
o153
 
7.2%
n134
 
6.3%
a130
 
6.1%
t123
 
5.8%
s108
 
5.1%
r102
 
4.8%
i88
 
4.1%
h71
 
3.3%
Other values (57)799
37.4%
Cyrillic
ValueCountFrequency (%)
и10
 
9.4%
о10
 
9.4%
е9
 
8.5%
т8
 
7.5%
н7
 
6.6%
к5
 
4.7%
с5
 
4.7%
а4
 
3.8%
С4
 
3.8%
ж3
 
2.8%
Other values (25)41
38.7%
None
ValueCountFrequency (%)
ø3
100.0%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Scripted
55 
Animation
26 
Reality
22 
Talk Show
11 
Documentary
Other values (6)

Length

Max length11
Median length10
Mean length8.276923077
Min length4

Characters and Unicode

Total characters1076
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)3.8%

Sample

1st rowReality
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted55
42.3%
Animation26
20.0%
Reality22
 
16.9%
Talk Show11
 
8.5%
Documentary9
 
6.9%
News2
 
1.5%
Variety1
 
0.8%
Panel Show1
 
0.8%
Award Show1
 
0.8%
Game Show1
 
0.8%

Length

2022-05-09T21:01:02.113760image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted55
38.2%
animation26
18.1%
reality22
 
15.3%
show14
 
9.7%
talk11
 
7.6%
documentary9
 
6.2%
news2
 
1.4%
variety1
 
0.7%
panel1
 
0.7%
award1
 
0.7%
Other values (2)2
 
1.4%

Most occurring characters

ValueCountFrequency (%)
i130
12.1%
t114
 
10.6%
e91
 
8.5%
a72
 
6.7%
S70
 
6.5%
r67
 
6.2%
c64
 
5.9%
n62
 
5.8%
p56
 
5.2%
d56
 
5.2%
Other values (18)294
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter918
85.3%
Uppercase Letter144
 
13.4%
Space Separator14
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i130
14.2%
t114
12.4%
e91
9.9%
a72
7.8%
r67
7.3%
c64
7.0%
n62
 
6.8%
p56
 
6.1%
d56
 
6.1%
o50
 
5.4%
Other values (8)156
17.0%
Uppercase Letter
ValueCountFrequency (%)
S70
48.6%
A27
 
18.8%
R22
 
15.3%
T11
 
7.6%
D9
 
6.2%
N2
 
1.4%
V1
 
0.7%
P1
 
0.7%
G1
 
0.7%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1062
98.7%
Common14
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i130
12.2%
t114
10.7%
e91
 
8.6%
a72
 
6.8%
S70
 
6.6%
r67
 
6.3%
c64
 
6.0%
n62
 
5.8%
p56
 
5.3%
d56
 
5.3%
Other values (17)280
26.4%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i130
12.1%
t114
 
10.6%
e91
 
8.5%
a72
 
6.7%
S70
 
6.5%
r67
 
6.2%
c64
 
5.9%
n62
 
5.8%
p56
 
5.2%
d56
 
5.2%
Other values (18)294
27.3%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
English
47 
Chinese
24 
Polish
13 
Russian
12 
Korean
Other values (8)
26 

Length

Max length10
Median length7
Mean length6.853846154
Min length4

Characters and Unicode

Total characters891
Distinct characters28
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.3%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English47
36.2%
Chinese24
18.5%
Polish13
 
10.0%
Russian12
 
9.2%
Korean8
 
6.2%
Norwegian8
 
6.2%
Arabic6
 
4.6%
Dutch4
 
3.1%
German3
 
2.3%
Portuguese2
 
1.5%
Other values (3)3
 
2.3%

Length

2022-05-09T21:01:02.252045image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english47
36.2%
chinese24
18.5%
polish13
 
10.0%
russian12
 
9.2%
korean8
 
6.2%
norwegian8
 
6.2%
arabic6
 
4.6%
dutch4
 
3.1%
german3
 
2.3%
portuguese2
 
1.5%
Other values (3)3
 
2.3%

Most occurring characters

ValueCountFrequency (%)
i112
12.6%
s111
12.5%
n103
11.6%
h90
10.1%
e71
8.0%
l61
 
6.8%
g59
 
6.6%
E47
 
5.3%
a41
 
4.6%
o32
 
3.6%
Other values (18)164
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter761
85.4%
Uppercase Letter130
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i112
14.7%
s111
14.6%
n103
13.5%
h90
11.8%
e71
9.3%
l61
8.0%
g59
7.8%
a41
 
5.4%
o32
 
4.2%
r27
 
3.5%
Other values (7)54
7.1%
Uppercase Letter
ValueCountFrequency (%)
E47
36.2%
C24
18.5%
P15
 
11.5%
R12
 
9.2%
K8
 
6.2%
N8
 
6.2%
A6
 
4.6%
D4
 
3.1%
G3
 
2.3%
T2
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Latin891
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i112
12.6%
s111
12.5%
n103
11.6%
h90
10.1%
e71
8.0%
l61
 
6.8%
g59
 
6.6%
E47
 
5.3%
a41
 
4.6%
o32
 
3.6%
Other values (18)164
18.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII891
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i112
12.6%
s111
12.5%
n103
11.6%
h90
10.1%
e71
8.0%
l61
 
6.8%
g59
 
6.6%
E47
 
5.3%
a41
 
4.6%
o32
 
3.6%
Other values (18)164
18.4%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct34
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
[]
31 
['Comedy']
16 
['Comedy', 'Horror']
13 
['Drama', 'Comedy']
11 
['Drama', 'Romance']
Other values (29)
50 

Length

Max length42
Median length39
Mean length15.6
Min length2

Characters and Unicode

Total characters2028
Distinct characters35
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)14.6%

Sample

1st row[]
2nd row['Drama', 'Comedy']
3rd row['Drama', 'Thriller']
4th row['Crime', 'Mystery']
5th row['Drama', 'Comedy', 'Romance']

Common Values

ValueCountFrequency (%)
[]31
23.8%
['Comedy']16
12.3%
['Comedy', 'Horror']13
10.0%
['Drama', 'Comedy']11
 
8.5%
['Drama', 'Romance']9
 
6.9%
['Drama', 'Comedy', 'Romance']7
 
5.4%
['Drama']5
 
3.8%
['Romance']4
 
3.1%
['Sports']3
 
2.3%
['Comedy', 'Music']2
 
1.5%
Other values (24)29
22.3%

Length

2022-05-09T21:01:02.439834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
comedy55
24.7%
drama44
19.7%
31
13.9%
romance26
11.7%
horror13
 
5.8%
mystery6
 
2.7%
fantasy5
 
2.2%
thriller5
 
2.2%
adventure5
 
2.2%
crime4
 
1.8%
Other values (12)29
13.0%

Most occurring characters

ValueCountFrequency (%)
'384
18.9%
m134
 
6.6%
[130
 
6.4%
]130
 
6.4%
a128
 
6.3%
o124
 
6.1%
e124
 
6.1%
r118
 
5.8%
,93
 
4.6%
93
 
4.6%
Other values (25)570
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter998
49.2%
Other Punctuation477
23.5%
Uppercase Letter196
 
9.7%
Open Punctuation130
 
6.4%
Close Punctuation130
 
6.4%
Space Separator93
 
4.6%
Dash Punctuation4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m134
13.4%
a128
12.8%
o124
12.4%
e124
12.4%
r118
11.8%
y75
7.5%
d65
6.5%
n55
5.5%
c45
 
4.5%
i38
 
3.8%
Other values (8)92
9.2%
Uppercase Letter
ValueCountFrequency (%)
C62
31.6%
D44
22.4%
R26
13.3%
H15
 
7.7%
A13
 
6.6%
F12
 
6.1%
M9
 
4.6%
S7
 
3.6%
T6
 
3.1%
L1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
'384
80.5%
,93
 
19.5%
Open Punctuation
ValueCountFrequency (%)
[130
100.0%
Close Punctuation
ValueCountFrequency (%)
]130
100.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1194
58.9%
Common834
41.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m134
11.2%
a128
10.7%
o124
10.4%
e124
10.4%
r118
9.9%
y75
 
6.3%
d65
 
5.4%
C62
 
5.2%
n55
 
4.6%
c45
 
3.8%
Other values (19)264
22.1%
Common
ValueCountFrequency (%)
'384
46.0%
[130
 
15.6%
]130
 
15.6%
,93
 
11.2%
93
 
11.2%
-4
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2028
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'384
18.9%
m134
 
6.6%
[130
 
6.4%
]130
 
6.4%
a128
 
6.3%
o124
 
6.1%
e124
 
6.1%
r118
 
5.8%
,93
 
4.6%
93
 
4.6%
Other values (25)570
28.1%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Running
59 
Ended
46 
To Be Determined
25 

Length

Max length16
Median length7
Mean length8.023076923
Min length5

Characters and Unicode

Total characters1043
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowTo Be Determined
5th rowEnded

Common Values

ValueCountFrequency (%)
Running59
45.4%
Ended46
35.4%
To Be Determined25
19.2%

Length

2022-05-09T21:01:02.608768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:01:02.752866image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running59
32.8%
ended46
25.6%
to25
13.9%
be25
13.9%
determined25
13.9%

Most occurring characters

ValueCountFrequency (%)
n248
23.8%
e146
14.0%
d117
11.2%
i84
 
8.1%
R59
 
5.7%
u59
 
5.7%
g59
 
5.7%
50
 
4.8%
E46
 
4.4%
T25
 
2.4%
Other values (6)150
14.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter813
77.9%
Uppercase Letter180
 
17.3%
Space Separator50
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n248
30.5%
e146
18.0%
d117
14.4%
i84
 
10.3%
u59
 
7.3%
g59
 
7.3%
o25
 
3.1%
t25
 
3.1%
r25
 
3.1%
m25
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
R59
32.8%
E46
25.6%
T25
13.9%
B25
13.9%
D25
13.9%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin993
95.2%
Common50
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n248
25.0%
e146
14.7%
d117
11.8%
i84
 
8.5%
R59
 
5.9%
u59
 
5.9%
g59
 
5.9%
E46
 
4.6%
T25
 
2.5%
o25
 
2.5%
Other values (5)125
12.6%
Common
ValueCountFrequency (%)
50
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1043
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n248
23.8%
e146
14.0%
d117
11.2%
i84
 
8.1%
R59
 
5.7%
u59
 
5.7%
g59
 
5.7%
50
 
4.8%
E46
 
4.4%
T25
 
2.4%
Other values (6)150
14.4%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)26.7%
Missing40
Missing (%)30.8%
Infinite0
Infinite (%)0.0%
Mean37.37777778
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:02.884470image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile11
Q115
median30
Q345
95-th percentile60
Maximum300
Range298
Interquartile range (IQR)30

Descriptive statistics

Standard deviation40.30796553
Coefficient of variation (CV)1.078393846
Kurtosis26.51364082
Mean37.37777778
Median Absolute Deviation (MAD)15
Skewness4.663357083
Sum3364
Variance1624.732085
MonotonicityNot monotonic
2022-05-09T21:01:03.042745image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4523
17.7%
1214
 
10.8%
208
 
6.2%
606
 
4.6%
306
 
4.6%
115
 
3.8%
403
 
2.3%
253
 
2.3%
503
 
2.3%
153
 
2.3%
Other values (14)16
 
12.3%
(Missing)40
30.8%
ValueCountFrequency (%)
21
 
0.8%
81
 
0.8%
101
 
0.8%
115
 
3.8%
1214
10.8%
153
 
2.3%
161
 
0.8%
181
 
0.8%
192
 
1.5%
208
6.2%
ValueCountFrequency (%)
3001
 
0.8%
2401
 
0.8%
1201
 
0.8%
621
 
0.8%
606
 
4.6%
531
 
0.8%
521
 
0.8%
503
 
2.3%
4523
17.7%
403
 
2.3%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct40
Distinct (%)33.6%
Missing11
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean35.86554622
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:03.219757image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile9
Q113
median31
Q345
95-th percentile60
Maximum300
Range298
Interquartile range (IQR)32

Descriptive statistics

Standard deviation35.15122882
Coefficient of variation (CV)0.9800834653
Kurtosis31.26910829
Mean35.86554622
Median Absolute Deviation (MAD)16
Skewness4.761346882
Sum4268
Variance1235.608888
MonotonicityNot monotonic
2022-05-09T21:01:03.374047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
4523
17.7%
1215
 
11.5%
96
 
4.6%
435
 
3.8%
515
 
3.8%
205
 
3.8%
605
 
3.8%
504
 
3.1%
143
 
2.3%
253
 
2.3%
Other values (30)45
34.6%
(Missing)11
 
8.5%
ValueCountFrequency (%)
22
 
1.5%
61
 
0.8%
81
 
0.8%
96
 
4.6%
102
 
1.5%
112
 
1.5%
1215
11.5%
132
 
1.5%
143
 
2.3%
152
 
1.5%
ValueCountFrequency (%)
3001
 
0.8%
2111
 
0.8%
1201
 
0.8%
771
 
0.8%
621
 
0.8%
605
3.8%
572
 
1.5%
561
 
0.8%
541
 
0.8%
531
 
0.8%

_embedded_show_premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct65
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-03
28 
2020-11-12
10 
2020-11-19
 
7
2020-11-26
 
6
2020-11-05
 
5
Other values (60)
74 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1300
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)40.0%

Sample

1st row2019-03-25
2nd row2020-03-26
3rd row2020-11-05
4th row2020-10-22
5th row2020-11-12

Common Values

ValueCountFrequency (%)
2020-12-0328
21.5%
2020-11-1210
 
7.7%
2020-11-197
 
5.4%
2020-11-266
 
4.6%
2020-11-055
 
3.8%
2020-05-275
 
3.8%
2020-11-184
 
3.1%
2020-10-293
 
2.3%
2013-02-012
 
1.5%
2020-11-302
 
1.5%
Other values (55)58
44.6%

Length

2022-05-09T21:01:03.650576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0328
21.5%
2020-11-1210
 
7.7%
2020-11-197
 
5.4%
2020-11-266
 
4.6%
2020-11-055
 
3.8%
2020-05-275
 
3.8%
2020-11-184
 
3.1%
2020-10-293
 
2.3%
2020-12-022
 
1.5%
2020-11-232
 
1.5%
Other values (55)58
44.6%

Most occurring characters

ValueCountFrequency (%)
0339
26.1%
2309
23.8%
-260
20.0%
1215
16.5%
350
 
3.8%
934
 
2.6%
524
 
1.8%
421
 
1.6%
616
 
1.2%
716
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1040
80.0%
Dash Punctuation260
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0339
32.6%
2309
29.7%
1215
20.7%
350
 
4.8%
934
 
3.3%
524
 
2.3%
421
 
2.0%
616
 
1.5%
716
 
1.5%
816
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
-260
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0339
26.1%
2309
23.8%
-260
20.0%
1215
16.5%
350
 
3.8%
934
 
2.6%
524
 
1.8%
421
 
1.6%
616
 
1.2%
716
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0339
26.1%
2309
23.8%
-260
20.0%
1215
16.5%
350
 
3.8%
934
 
2.6%
524
 
1.8%
421
 
1.6%
616
 
1.2%
716
 
1.2%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
84 
2020-12-03
 
7
2020-12-10
 
7
2020-12-17
 
6
2020-12-24
 
5
Other values (13)
21 

Length

Max length10
Median length3
Mean length5.476923077
Min length3

Characters and Unicode

Total characters712
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.6%

Sample

1st rownan
2nd row2021-01-21
3rd row2020-12-24
4th rownan
5th row2020-12-03

Common Values

ValueCountFrequency (%)
nan84
64.6%
2020-12-037
 
5.4%
2020-12-107
 
5.4%
2020-12-176
 
4.6%
2020-12-245
 
3.8%
2020-12-113
 
2.3%
2021-01-142
 
1.5%
2020-12-162
 
1.5%
2021-01-272
 
1.5%
2020-12-302
 
1.5%
Other values (8)10
 
7.7%

Length

2022-05-09T21:01:03.773160image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan84
64.6%
2020-12-037
 
5.4%
2020-12-107
 
5.4%
2020-12-176
 
4.6%
2020-12-245
 
3.8%
2020-12-113
 
2.3%
2021-01-042
 
1.5%
2020-12-082
 
1.5%
2020-12-302
 
1.5%
2021-01-272
 
1.5%
Other values (8)10
 
7.7%

Most occurring characters

ValueCountFrequency (%)
n168
23.6%
2140
19.7%
0113
15.9%
-92
12.9%
a84
11.8%
180
11.2%
39
 
1.3%
79
 
1.3%
49
 
1.3%
64
 
0.6%
Other values (2)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number368
51.7%
Lowercase Letter252
35.4%
Dash Punctuation92
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2140
38.0%
0113
30.7%
180
21.7%
39
 
2.4%
79
 
2.4%
49
 
2.4%
64
 
1.1%
83
 
0.8%
51
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
n168
66.7%
a84
33.3%
Dash Punctuation
ValueCountFrequency (%)
-92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common460
64.6%
Latin252
35.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2140
30.4%
0113
24.6%
-92
20.0%
180
17.4%
39
 
2.0%
79
 
2.0%
49
 
2.0%
64
 
0.9%
83
 
0.7%
51
 
0.2%
Latin
ValueCountFrequency (%)
n168
66.7%
a84
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n168
23.6%
2140
19.7%
0113
15.9%
-92
12.9%
a84
11.8%
180
11.2%
39
 
1.3%
79
 
1.3%
49
 
1.3%
64
 
0.6%
Other values (2)4
 
0.6%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct76
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
22 
https://www.netflix.com/title/81297404
13 
https://www.hbomax.com/looney-tunes/
 
5
https://www.hbomax.com/heavens-gate
 
4
https://v.qq.com/detail/m/mzc00200gbahyn5.html
 
4
Other values (71)
82 

Length

Max length119
Median length74
Mean length40.17692308
Min length3

Characters and Unicode

Total characters5223
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)46.9%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://start.ru/watch/257-prichin-chtoby-zhit
3rd rowhttps://more.tv/psih
4th rowhttps://start.ru/watch/sherlok-v-rossii
5th rowhttps://www.ivi.ru/watch/nezhnost

Common Values

ValueCountFrequency (%)
nan22
 
16.9%
https://www.netflix.com/title/8129740413
 
10.0%
https://www.hbomax.com/looney-tunes/5
 
3.8%
https://www.hbomax.com/heavens-gate4
 
3.1%
https://v.qq.com/detail/m/mzc00200gbahyn5.html4
 
3.1%
https://play.hbomax.com/series/urn:hbo:series:GX6MzzwZycJYSwwEAAALF3
 
2.3%
https://tv.nrk.no/serie/ukjent-arving2
 
1.5%
https://www.joyn.de/serien/stichtag2
 
1.5%
https://play.hbomax.com/page/urn:hbo:page:GX5MHsQzwwIuLwgEAAACp:type:series2
 
1.5%
https://www.iqiyi.com/a_19rrhskr95.html2
 
1.5%
Other values (66)71
54.6%

Length

2022-05-09T21:01:03.932900image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan22
 
16.9%
https://www.netflix.com/title/8129740413
 
10.0%
https://www.hbomax.com/looney-tunes5
 
3.8%
https://www.hbomax.com/heavens-gate4
 
3.1%
https://v.qq.com/detail/m/mzc00200gbahyn5.html4
 
3.1%
https://play.hbomax.com/series/urn:hbo:series:gx6mzzwzycjyswweaaalf3
 
2.3%
https://www.hbomax.com/coming-soon/full-bloom2
 
1.5%
https://www.iqiyi.com/lib/m_213579814.html2
 
1.5%
https://so.youku.com/search_video/q_%e9%a2%84%e6%94%af%e6%9c%aa%e6%9d%a5?spm=a2hbt.13141534.left-title-content-wrap.5~a2
 
1.5%
https://shahid.mbc.net/en/series/masrah-masr/series-8167492
 
1.5%
Other values (66)71
54.6%

Most occurring characters

ValueCountFrequency (%)
/442
 
8.5%
t429
 
8.2%
s269
 
5.2%
e257
 
4.9%
o235
 
4.5%
w229
 
4.4%
.218
 
4.2%
h217
 
4.2%
a190
 
3.6%
n190
 
3.6%
Other values (64)2547
48.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3533
67.6%
Other Punctuation846
 
16.2%
Decimal Number421
 
8.1%
Uppercase Letter301
 
5.8%
Dash Punctuation95
 
1.8%
Math Symbol15
 
0.3%
Connector Punctuation12
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t429
 
12.1%
s269
 
7.6%
e257
 
7.3%
o235
 
6.7%
w229
 
6.5%
h217
 
6.1%
a190
 
5.4%
n190
 
5.4%
p169
 
4.8%
i167
 
4.7%
Other values (16)1181
33.4%
Uppercase Letter
ValueCountFrequency (%)
A40
 
13.3%
E20
 
6.6%
D17
 
5.6%
L16
 
5.3%
P16
 
5.3%
C16
 
5.3%
S15
 
5.0%
M15
 
5.0%
F13
 
4.3%
Z13
 
4.3%
Other values (16)120
39.9%
Decimal Number
ValueCountFrequency (%)
459
14.0%
954
12.8%
052
12.4%
148
11.4%
843
10.2%
240
9.5%
636
8.6%
730
7.1%
530
7.1%
329
6.9%
Other Punctuation
ValueCountFrequency (%)
/442
52.2%
.218
25.8%
:130
 
15.4%
%42
 
5.0%
?11
 
1.3%
&1
 
0.1%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=12
80.0%
~3
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
-95
100.0%
Connector Punctuation
ValueCountFrequency (%)
_12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3834
73.4%
Common1389
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t429
 
11.2%
s269
 
7.0%
e257
 
6.7%
o235
 
6.1%
w229
 
6.0%
h217
 
5.7%
a190
 
5.0%
n190
 
5.0%
p169
 
4.4%
i167
 
4.4%
Other values (42)1482
38.7%
Common
ValueCountFrequency (%)
/442
31.8%
.218
15.7%
:130
 
9.4%
-95
 
6.8%
459
 
4.2%
954
 
3.9%
052
 
3.7%
148
 
3.5%
843
 
3.1%
%42
 
3.0%
Other values (12)206
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII5223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/442
 
8.5%
t429
 
8.2%
s269
 
5.2%
e257
 
4.9%
o235
 
4.5%
w229
 
4.4%
.218
 
4.2%
h217
 
4.2%
a190
 
3.6%
n190
 
3.6%
Other values (64)2547
48.8%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct57
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.57692308
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:04.100351image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18.5
median32
Q354.75
95-th percentile87
Maximum100
Range99
Interquartile range (IQR)46.25

Descriptive statistics

Standard deviation28.96077684
Coefficient of variation (CV)0.7917772848
Kurtosis-0.8136753653
Mean36.57692308
Median Absolute Deviation (MAD)23
Skewness0.5519441127
Sum4755
Variance838.7265951
MonotonicityNot monotonic
2022-05-09T21:01:04.265107image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
314
 
10.8%
2511
 
8.5%
448
 
6.2%
26
 
4.6%
85
 
3.8%
855
 
3.8%
144
 
3.1%
344
 
3.1%
184
 
3.1%
474
 
3.1%
Other values (47)65
50.0%
ValueCountFrequency (%)
13
 
2.3%
26
4.6%
314
10.8%
41
 
0.8%
62
 
1.5%
72
 
1.5%
85
 
3.8%
101
 
0.8%
111
 
0.8%
144
 
3.1%
ValueCountFrequency (%)
1003
2.3%
932
 
1.5%
901
 
0.8%
872
 
1.5%
855
3.8%
841
 
0.8%
832
 
1.5%
791
 
0.8%
781
 
0.8%
771
 
0.8%

_embedded_show_dvdCountry
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
129 
{'name': 'Korea, Republic of', 'code': 'KR', 'timezone': 'Asia/Seoul'}
 
1

Length

Max length70
Median length3
Mean length3.515384615
Min length3

Characters and Unicode

Total characters457
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan129
99.2%
{'name': 'Korea, Republic of', 'code': 'KR', 'timezone': 'Asia/Seoul'}1
 
0.8%

Length

2022-05-09T21:01:04.391348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:01:04.508253image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan129
94.2%
name1
 
0.7%
korea1
 
0.7%
republic1
 
0.7%
of1
 
0.7%
code1
 
0.7%
kr1
 
0.7%
timezone1
 
0.7%
asia/seoul1
 
0.7%

Most occurring characters

ValueCountFrequency (%)
n260
56.9%
a132
28.9%
'12
 
2.6%
e7
 
1.5%
7
 
1.5%
o5
 
1.1%
i3
 
0.7%
:3
 
0.7%
,3
 
0.7%
R2
 
0.4%
Other values (18)23
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter423
92.6%
Other Punctuation19
 
4.2%
Space Separator7
 
1.5%
Uppercase Letter6
 
1.3%
Open Punctuation1
 
0.2%
Close Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n260
61.5%
a132
31.2%
e7
 
1.7%
o5
 
1.2%
i3
 
0.7%
c2
 
0.5%
l2
 
0.5%
u2
 
0.5%
m2
 
0.5%
p1
 
0.2%
Other values (7)7
 
1.7%
Other Punctuation
ValueCountFrequency (%)
'12
63.2%
:3
 
15.8%
,3
 
15.8%
/1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
K2
33.3%
A1
16.7%
S1
16.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
{1
100.0%
Close Punctuation
ValueCountFrequency (%)
}1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin429
93.9%
Common28
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n260
60.6%
a132
30.8%
e7
 
1.6%
o5
 
1.2%
i3
 
0.7%
R2
 
0.5%
c2
 
0.5%
l2
 
0.5%
u2
 
0.5%
K2
 
0.5%
Other values (11)12
 
2.8%
Common
ValueCountFrequency (%)
'12
42.9%
7
25.0%
:3
 
10.7%
,3
 
10.7%
{1
 
3.6%
/1
 
3.6%
}1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII457
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n260
56.9%
a132
28.9%
'12
 
2.6%
e7
 
1.5%
7
 
1.5%
o5
 
1.1%
i3
 
0.7%
:3
 
0.7%
,3
 
0.7%
R2
 
0.4%
Other values (18)23
 
5.0%

_embedded_show_summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct72
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
18 
<p>No demon is safe as Bogdan Boner, the alcohol-loving, self-taught exorcist-for-hire, returns with more inventive, obscene and deadly deeds.</p>
13 
<p><b>Stylish with Jenna Lyons</b> follows Jenna as she tackles design projects that will help define her future business. Join her in this ambitious new venture, delivering a masterclass in taste, design, and fashion in every episode.</p>
 
8
<p><b>Looney Tunes Cartoons</b>, an all-new series from Warner Bros. Animation starring the cherished <i>Looney Tunes</i> characters. <i>Looney Tunes Cartoons </i>echoes the high production value and process of the original Looney Tunes theatrical shorts with a cartoonist-driven approach to storytelling. Marquee <i>Looney Tunes</i> characters will be featured in their classic pairings in simple, gag-driven and visually vibrant stories. The new series will include 80 eleven-minute episodes, each comprised of animated shorts that vary in length and include adapted storylines for today's audience.</p>
 
5
<p>A young cartoonist intentionally gets near Ji Yan Xin, a cold and arrogant professor. Qi Nian, a girl with a straightforward personality hopes that interacting with Ji Yan Xin would give her inspiration and creative materials for her comic plot. Coincidentally Ji Yan Xin's younger brother Ji Si Qi becomes Qi Nian's assistant and a catalyst for their relationship to progress and blossom.</p>
 
4
Other values (67)
82 

Length

Max length1084
Median length611.5
Mean length301.6076923
Min length3

Characters and Unicode

Total characters39209
Distinct characters90
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)42.3%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>
3rd row<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan18
 
13.8%
<p>No demon is safe as Bogdan Boner, the alcohol-loving, self-taught exorcist-for-hire, returns with more inventive, obscene and deadly deeds.</p>13
 
10.0%
<p><b>Stylish with Jenna Lyons</b> follows Jenna as she tackles design projects that will help define her future business. Join her in this ambitious new venture, delivering a masterclass in taste, design, and fashion in every episode.</p>8
 
6.2%
<p><b>Looney Tunes Cartoons</b>, an all-new series from Warner Bros. Animation starring the cherished <i>Looney Tunes</i> characters. <i>Looney Tunes Cartoons </i>echoes the high production value and process of the original Looney Tunes theatrical shorts with a cartoonist-driven approach to storytelling. Marquee <i>Looney Tunes</i> characters will be featured in their classic pairings in simple, gag-driven and visually vibrant stories. The new series will include 80 eleven-minute episodes, each comprised of animated shorts that vary in length and include adapted storylines for today's audience.</p>5
 
3.8%
<p>A young cartoonist intentionally gets near Ji Yan Xin, a cold and arrogant professor. Qi Nian, a girl with a straightforward personality hopes that interacting with Ji Yan Xin would give her inspiration and creative materials for her comic plot. Coincidentally Ji Yan Xin's younger brother Ji Si Qi becomes Qi Nian's assistant and a catalyst for their relationship to progress and blossom.</p>4
 
3.1%
<p><b>Heaven's Gate: The Cult of Cults</b> is a thorough examination of the infamous UFO cult through the eyes of its former members and loved ones. What started in 1975 with the disappearance of 20 people from a small town in Oregon, ended in 1997 with the largest suicide on US soil and changed the face of modern New Age religion forever. This four-part docuseries uses never-before-seen footage and first-person accounts to explore the infamous UFO cult that shocked the nation with their out-of-this-world beliefs.</p>4
 
3.1%
<p><b>12 Dates of Christmas</b> is a holiday-inspired dating series set in a stunning winter wonderland. The series follows a cast of singles as they step into a real-life romantic comedy full of cozy sweaters, fireside cuddles, and mistletoe kisses, all arranged to help these souls find love - just in time for the holidays.</p>3
 
2.3%
<p>A collection of comedy theater presents a new type of separate plays in titles and events with each episode.</p>2
 
1.5%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>2
 
1.5%
<p>With incredible artistic creations and floristry face-offs, <b>Full Bloom</b> will allow audiences to escape into a surreal world as contestants will design and execute some of the most wondrous, Wonka-esq floral creations ever seen. Each episode features themed challenges centered around a unique stem of the floristry world including fashion, art, events and weddings.</p>2
 
1.5%
Other values (62)69
53.1%

Length

2022-05-09T21:01:04.618349image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the302
 
4.8%
and245
 
3.9%
a198
 
3.1%
of161
 
2.5%
in141
 
2.2%
to117
 
1.8%
with98
 
1.5%
is83
 
1.3%
as58
 
0.9%
her56
 
0.9%
Other values (1805)4869
76.9%

Most occurring characters

ValueCountFrequency (%)
6192
15.8%
e3667
 
9.4%
n2433
 
6.2%
a2413
 
6.2%
i2368
 
6.0%
t2311
 
5.9%
o2223
 
5.7%
s2146
 
5.5%
r1827
 
4.7%
h1507
 
3.8%
Other values (80)12122
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter29639
75.6%
Space Separator6199
 
15.8%
Uppercase Letter1197
 
3.1%
Other Punctuation1068
 
2.7%
Math Symbol800
 
2.0%
Dash Punctuation166
 
0.4%
Decimal Number111
 
0.3%
Format14
 
< 0.1%
Open Punctuation7
 
< 0.1%
Close Punctuation7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3667
12.4%
n2433
 
8.2%
a2413
 
8.1%
i2368
 
8.0%
t2311
 
7.8%
o2223
 
7.5%
s2146
 
7.2%
r1827
 
6.2%
h1507
 
5.1%
l1261
 
4.3%
Other values (21)7483
25.2%
Uppercase Letter
ValueCountFrequency (%)
T137
 
11.4%
S107
 
8.9%
L78
 
6.5%
B75
 
6.3%
J67
 
5.6%
A64
 
5.3%
C64
 
5.3%
M54
 
4.5%
N51
 
4.3%
W47
 
3.9%
Other values (16)453
37.8%
Other Punctuation
ValueCountFrequency (%)
,390
36.5%
.317
29.7%
/209
19.6%
'84
 
7.9%
"20
 
1.9%
!14
 
1.3%
:13
 
1.2%
?9
 
0.8%
;4
 
0.4%
4
 
0.4%
Other values (2)4
 
0.4%
Decimal Number
ValueCountFrequency (%)
029
26.1%
118
16.2%
218
16.2%
912
10.8%
710
 
9.0%
58
 
7.2%
86
 
5.4%
44
 
3.6%
63
 
2.7%
33
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
-152
91.6%
9
 
5.4%
5
 
3.0%
Space Separator
ValueCountFrequency (%)
6192
99.9%
 7
 
0.1%
Math Symbol
ValueCountFrequency (%)
<400
50.0%
>400
50.0%
Format
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
(7
100.0%
Close Punctuation
ValueCountFrequency (%)
)7
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin30836
78.6%
Common8373
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3667
11.9%
n2433
 
7.9%
a2413
 
7.8%
i2368
 
7.7%
t2311
 
7.5%
o2223
 
7.2%
s2146
 
7.0%
r1827
 
5.9%
h1507
 
4.9%
l1261
 
4.1%
Other values (47)8680
28.1%
Common
ValueCountFrequency (%)
6192
74.0%
<400
 
4.8%
>400
 
4.8%
,390
 
4.7%
.317
 
3.8%
/209
 
2.5%
-152
 
1.8%
'84
 
1.0%
029
 
0.3%
"20
 
0.2%
Other values (23)180
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII39163
99.9%
Punctuation33
 
0.1%
None13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6192
15.8%
e3667
 
9.4%
n2433
 
6.2%
a2413
 
6.2%
i2368
 
6.0%
t2311
 
5.9%
o2223
 
5.7%
s2146
 
5.5%
r1827
 
4.7%
h1507
 
3.8%
Other values (69)12076
30.8%
Punctuation
ValueCountFrequency (%)
14
42.4%
9
27.3%
5
 
15.2%
4
 
12.1%
1
 
3.0%
None
ValueCountFrequency (%)
 7
53.8%
ø2
 
15.4%
ê1
 
7.7%
ã1
 
7.7%
å1
 
7.7%
é1
 
7.7%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION

Distinct86
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1636461356
Minimum1607104092
Maximum1652126507
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:01:04.741708image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1607104092
5-th percentile1608129919
Q11625846145
median1644546182
Q31649684316
95-th percentile1651961154
Maximum1652126507
Range45022415
Interquartile range (IQR)23838171.25

Descriptive statistics

Standard deviation15390643.9
Coefficient of variation (CV)0.009404831857
Kurtosis-0.879621353
Mean1636461356
Median Absolute Deviation (MAD)7446869.5
Skewness-0.7617056847
Sum2.127399763 × 1011
Variance2.368719196 × 1014
MonotonicityNot monotonic
2022-05-09T21:01:04.876164image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
163415135113
 
10.0%
16496843168
 
6.2%
16461505445
 
3.8%
16467471974
 
3.1%
16167843834
 
3.1%
16511100903
 
2.3%
16357351792
 
1.5%
16096410182
 
1.5%
16196334992
 
1.5%
16508264802
 
1.5%
Other values (76)85
65.4%
ValueCountFrequency (%)
16071040921
0.8%
16071675851
0.8%
16076383811
0.8%
16076387711
0.8%
16076979652
1.5%
16079646561
0.8%
16083319081
0.8%
16083343021
0.8%
16084990071
0.8%
16096068541
0.8%
ValueCountFrequency (%)
16521265071
0.8%
16520679312
1.5%
16520354301
0.8%
16520165431
0.8%
16520047591
0.8%
16519813431
0.8%
16519364791
0.8%
16519333291
0.8%
16519332091
0.8%
16518386471
0.8%

_links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2001668
 
1
https://api.tvmaze.com/episodes/2001666
 
1
https://api.tvmaze.com/episodes/2001665
 
1
https://api.tvmaze.com/episodes/2000073
 
1
Other values (125)
125 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters5070
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/20016681
 
0.8%
https://api.tvmaze.com/episodes/20016661
 
0.8%
https://api.tvmaze.com/episodes/20016651
 
0.8%
https://api.tvmaze.com/episodes/20000731
 
0.8%
https://api.tvmaze.com/episodes/20000721
 
0.8%
https://api.tvmaze.com/episodes/19975381
 
0.8%
https://api.tvmaze.com/episodes/19975371
 
0.8%
https://api.tvmaze.com/episodes/19884051
 
0.8%
https://api.tvmaze.com/episodes/19854841
 
0.8%
Other values (120)120
92.3%

Length

2022-05-09T21:01:04.994091image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/23122231
 
0.8%
https://api.tvmaze.com/episodes/19954051
 
0.8%
https://api.tvmaze.com/episodes/20077601
 
0.8%
https://api.tvmaze.com/episodes/19857891
 
0.8%
https://api.tvmaze.com/episodes/20396221
 
0.8%
https://api.tvmaze.com/episodes/20396231
 
0.8%
https://api.tvmaze.com/episodes/23244271
 
0.8%
https://api.tvmaze.com/episodes/23244281
 
0.8%
https://api.tvmaze.com/episodes/23244291
 
0.8%
Other values (120)120
92.3%

Most occurring characters

ValueCountFrequency (%)
/520
 
10.3%
p390
 
7.7%
s390
 
7.7%
e390
 
7.7%
t390
 
7.7%
o260
 
5.1%
a260
 
5.1%
i260
 
5.1%
.260
 
5.1%
m260
 
5.1%
Other values (16)1690
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3250
64.1%
Other Punctuation910
 
17.9%
Decimal Number910
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p390
12.0%
s390
12.0%
e390
12.0%
t390
12.0%
o260
8.0%
a260
8.0%
i260
8.0%
m260
8.0%
h130
 
4.0%
d130
 
4.0%
Other values (3)390
12.0%
Decimal Number
ValueCountFrequency (%)
9141
15.5%
2140
15.4%
0121
13.3%
1110
12.1%
378
8.6%
674
8.1%
871
7.8%
461
6.7%
760
6.6%
554
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/520
57.1%
.260
28.6%
:130
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3250
64.1%
Common1820
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/520
28.6%
.260
14.3%
9141
 
7.7%
2140
 
7.7%
:130
 
7.1%
0121
 
6.6%
1110
 
6.0%
378
 
4.3%
674
 
4.1%
871
 
3.9%
Other values (3)175
 
9.6%
Latin
ValueCountFrequency (%)
p390
12.0%
s390
12.0%
e390
12.0%
t390
12.0%
o260
8.0%
a260
8.0%
i260
8.0%
m260
8.0%
h130
 
4.0%
d130
 
4.0%
Other values (3)390
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/520
 
10.3%
p390
 
7.7%
s390
 
7.7%
e390
 
7.7%
t390
 
7.7%
o260
 
5.1%
a260
 
5.1%
i260
 
5.1%
.260
 
5.1%
m260
 
5.1%
Other values (16)1690
33.3%

Interactions

2022-05-09T21:00:54.284950image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:27.335598image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:33.813060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:37.123807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:39.734621image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:42.151076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:46.910146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:48.999256image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:51.635338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:55.557528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:28.846136image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:35.105872image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:38.351765image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:40.838411image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:43.557978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:47.687657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:50.061977image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:52.836887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:55.671079image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:29.398382image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:35.248563image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:38.457751image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:40.933710image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:43.969506image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:47.788794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:50.177643image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:52.936355image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:55.771490image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:29.939209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:35.487528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:38.564828image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:41.028409image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:44.292768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:47.881328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:50.291786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:53.139591image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:55.875955image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:30.409549image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:35.599162image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:38.665132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:41.125479image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:44.737067image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:47.981447image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:50.417746image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:53.231495image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:56.792689image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:31.602809image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:36.427872image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:39.317358image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:41.762233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:45.629437image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:48.623970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:51.183073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:53.894653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:56.947978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:31.989208image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:36.583660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:39.415052image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:41.860540image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:45.886908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:48.723434image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:51.301501image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:53.985410image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:57.071719image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:32.498165image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:36.849875image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:39.522052image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:41.954670image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:46.235034image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:48.817498image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:51.405644image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:54.091689image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:57.185076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:33.114371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:37.001332image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:39.632453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:42.051660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:46.580945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:48.901363image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:51.512753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:00:54.184669image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:01:05.068270image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:01:05.218824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:01:05.396644image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:01:05.632377image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:01:06.024621image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:00:57.390689image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:00:58.334515image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:00:58.610586image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:00:58.800804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01979825https://www.tvmaze.com/episodes/1979825/sim-for-you-4x17-chanyeols-episode-17Chanyeol's Episode 174.017.0regular2020-12-0306:002020-12-02T21:00:00+00:0016.0None<p><b>#A refreshing break #I refuse any rewards #Going with the flow</b></p>41648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25nanhttps://www.vlive.tv/video/12163771.0nan<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1.608499e+09https://api.tvmaze.com/episodes/1977902
11963996https://www.tvmaze.com/episodes/1963996/257-pricin-ctoby-zit-2x06-seria-19Серия 192.06.0regular2020-12-03nan2020-12-03T00:00:00+00:0025.0Nonenan43722https://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit257 причин, чтобы житьScriptedRussian['Drama', 'Comedy']Ended25.024.02020-03-262021-01-21https://start.ru/watch/257-prichin-chtoby-zhit38.0nan<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>1.617284e+09https://api.tvmaze.com/episodes/2015818
21960726https://www.tvmaze.com/episodes/1960726/psih-1x05-revnostРевность1.05.0regular2020-12-0312:002020-12-03T00:00:00+00:0066.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752690.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752690.jpg'}nan49280https://www.tvmaze.com/shows/49280/psihПсихScriptedRussian['Drama', 'Thriller']Ended62.062.02020-11-052020-12-24https://more.tv/psih29.0nan<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>1.619195e+09https://api.tvmaze.com/episodes/1964000
31954453https://www.tvmaze.com/episodes/1954453/serlok-v-rossii-1x07-serdce-holmsa-iСердце Холмса I1.07.0regular2020-12-03nan2020-12-03T00:00:00+00:0050.0Nonenan49422https://www.tvmaze.com/shows/49422/serlok-v-rossiiШерлок в РоссииScriptedRussian['Crime', 'Mystery']To Be Determined52.051.02020-10-22nanhttps://start.ru/watch/sherlok-v-rossii38.0nannan1.643091e+09https://api.tvmaze.com/episodes/1995405
41969558https://www.tvmaze.com/episodes/1969558/neznost-1x10-seria-10Серия 101.010.0regular2020-12-03nan2020-12-03T00:00:00+00:0021.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/312/781439.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/312/781439.jpg'}nan51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian['Drama', 'Comedy', 'Romance']Ended19.019.02020-11-122020-12-03https://www.ivi.ru/watch/nezhnost2.0nannan1.620058e+09https://api.tvmaze.com/episodes/2007760
51969559https://www.tvmaze.com/episodes/1969559/neznost-1x11-seria-11Серия 111.011.0regular2020-12-03nan2020-12-03T00:00:00+00:0021.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/312/781441.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/312/781441.jpg'}nan51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian['Drama', 'Comedy', 'Romance']Ended19.019.02020-11-122020-12-03https://www.ivi.ru/watch/nezhnost2.0nannan1.620058e+09https://api.tvmaze.com/episodes/1985789
61979224https://www.tvmaze.com/episodes/1979224/kotiki-1x04-seria-4Серия 41.04.0regular2020-12-03nan2020-12-03T00:00:00+00:0013.0Nonenan52198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian['Comedy']Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki15.0nannan1.637555e+09https://api.tvmaze.com/episodes/2039622
71971568https://www.tvmaze.com/episodes/1971568/mermaid-prince-2x08-episode-8Episode 82.08.0regular2020-12-0311:002020-12-03T02:00:00+00:0015.0Nonenan47207https://www.tvmaze.com/shows/47207/mermaid-princeMermaid PrinceScriptedKorean['Drama', 'Romance', 'Mystery']Ended15.015.02020-04-142020-12-10nan34.0nan<p><b>Mermaid Prince</b> is about Hye Ri, who embarks on a graduation trip to Gangwon Province and meets Woo Hyuk, a mysterious guy who runs a guest house.</p>1.610205e+09https://api.tvmaze.com/episodes/2039623
81985785https://www.tvmaze.com/episodes/1985785/theres-a-pit-in-my-senior-martial-brothers-brain-2x07-episode-7Episode 72.07.0regular2020-12-0311:002020-12-03T03:00:00+00:0020.0Nonenan38031https://www.tvmaze.com/shows/38031/theres-a-pit-in-my-senior-martial-brothers-brainThere's a Pit in My Senior Martial Brother's BrainAnimationChinese['Comedy', 'Action', 'Adventure', 'Anime']Running20.010.02018-04-04nanhttps://www.bilibili.com/bangumi/media/md17632/23.0nannan1.607965e+09https://api.tvmaze.com/episodes/2324427
91944214https://www.tvmaze.com/episodes/1944214/quan-zhi-gao-shou-2x11-little-cold-handsLittle Cold Hands2.011.0regular2020-12-03nan2020-12-03T04:00:00+00:0020.0Nonenan24837https://www.tvmaze.com/shows/24837/quan-zhi-gao-shouQuan Zhi Gao ShouAnimationChinese['Comedy', 'Action', 'Adventure', 'Anime']Ended20.020.02017-04-062020-12-10https://v.qq.com/detail/3/3r7bnv3gdykfdok.html65.0nan<p>In the multiplayer online game Glory, Ye Xiu is regarded as a textbook and a top-tier pro-player. However, due to a myriad of reasons, he is kicked from the team. After leaving the pro scene, he finds work in an Internet Cafe as a manager. When Glory launches its tenth server, he throws himself in to the game once more. Possessing ten years of experience, the memories of his past, and an incomplete, self-made weapon, his return along the road to the summit begins!</p>1.607168e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
1202018675https://www.tvmaze.com/episodes/2018675/stylish-with-jenna-lyons-1x07-reinventing-date-nightReinventing Date Night1.07.0regular2020-12-03nan2020-12-03T17:00:00+00:00NaNNone<p>Emotions run high as the remaining associates divide into teams to help Jenna give three couples high-fashion date night transformations.</p>51845https://www.tvmaze.com/shows/51845/stylish-with-jenna-lyonsStylish with Jenna LyonsRealityEnglish[]RunningNaNNaN2020-12-03nannan25.0nan<p><b>Stylish with Jenna Lyons</b> follows Jenna as she tackles design projects that will help define her future business. Join her in this ambitious new venture, delivering a masterclass in taste, design, and fashion in every episode.</p>1.649684e+09https://api.tvmaze.com/episodes/2234296
1212018676https://www.tvmaze.com/episodes/2018676/stylish-with-jenna-lyons-1x08-dream-jobDream Job1.08.0regular2020-12-03nan2020-12-03T17:00:00+00:00NaNNone<p>The final associates design their own socially-distant pop-up experiences as they await Jenna's official hiring decision.</p>51845https://www.tvmaze.com/shows/51845/stylish-with-jenna-lyonsStylish with Jenna LyonsRealityEnglish[]RunningNaNNaN2020-12-03nannan25.0nan<p><b>Stylish with Jenna Lyons</b> follows Jenna as she tackles design projects that will help define her future business. Join her in this ambitious new venture, delivering a masterclass in taste, design, and fashion in every episode.</p>1.649684e+09https://api.tvmaze.com/episodes/2234297
1222008331https://www.tvmaze.com/episodes/2008331/for-the-love-of-jason-1x03-the-single-guyThe Single Guy1.03.0regular2020-12-03nan2020-12-03T17:00:00+00:0025.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732255.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732255.jpg'}<p>Erick's father makes a surprise weekend visit with the hopes of getting to know Lisa better. Patricia urges Jason and Alexandria to settle down. Jason reluctantly rolls solo to his married friends' get-together and the event quickly goes downhill.</p>51899https://www.tvmaze.com/shows/51899/for-the-love-of-jasonFor the Love of JasonScriptedEnglish['Drama']RunningNaN25.02020-11-19nanhttps://allblk.tv/fortheloveofjason/41.0nan<p>Jason has always had it together. He's educated and financially stable with no baby mama drama. When he broke off his longtime relationship, he got caught up in the bachelor lifestyle, not realizing life was passing him by. One by one, his friends start settling down, leaving Jason the odd man out. He now feels pressure to catch up and finds himself in awkward dating encounters with women. Through it all, his friends are there to help him along the way.</p>1.646530e+09https://api.tvmaze.com/episodes/2236494
1231974910https://www.tvmaze.com/episodes/1974910/heavens-gate-the-cult-of-cults-1x01-the-awakeningThe Awakening1.01.0regular2020-12-03nan2020-12-03T17:00:00+00:0049.0Nonenan52071https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cultsHeaven's Gate: The Cult of CultsDocumentaryEnglish[]EndedNaN51.02020-12-032020-12-03https://www.hbomax.com/heavens-gate47.0nan<p><b>Heaven's Gate: The Cult of Cults</b> is a thorough examination of the infamous UFO cult through the eyes of its former members and loved ones. What started in 1975 with the disappearance of 20 people from a small town in Oregon, ended in 1997 with the largest suicide on US soil and changed the face of modern New Age religion forever. This four-part docuseries uses never-before-seen footage and first-person accounts to explore the infamous UFO cult that shocked the nation with their out-of-this-world beliefs.</p>1.616784e+09https://api.tvmaze.com/episodes/1977423
1241974911https://www.tvmaze.com/episodes/1974911/heavens-gate-the-cult-of-cults-1x02-the-chrysalisThe Chrysalis1.02.0regular2020-12-03nan2020-12-03T17:00:00+00:0050.0Nonenan52071https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cultsHeaven's Gate: The Cult of CultsDocumentaryEnglish[]EndedNaN51.02020-12-032020-12-03https://www.hbomax.com/heavens-gate47.0nan<p><b>Heaven's Gate: The Cult of Cults</b> is a thorough examination of the infamous UFO cult through the eyes of its former members and loved ones. What started in 1975 with the disappearance of 20 people from a small town in Oregon, ended in 1997 with the largest suicide on US soil and changed the face of modern New Age religion forever. This four-part docuseries uses never-before-seen footage and first-person accounts to explore the infamous UFO cult that shocked the nation with their out-of-this-world beliefs.</p>1.616784e+09https://api.tvmaze.com/episodes/1976649
1251974912https://www.tvmaze.com/episodes/1974912/heavens-gate-the-cult-of-cults-1x03-the-second-harvestThe Second Harvest1.03.0regular2020-12-03nan2020-12-03T17:00:00+00:0052.0Nonenan52071https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cultsHeaven's Gate: The Cult of CultsDocumentaryEnglish[]EndedNaN51.02020-12-032020-12-03https://www.hbomax.com/heavens-gate47.0nan<p><b>Heaven's Gate: The Cult of Cults</b> is a thorough examination of the infamous UFO cult through the eyes of its former members and loved ones. What started in 1975 with the disappearance of 20 people from a small town in Oregon, ended in 1997 with the largest suicide on US soil and changed the face of modern New Age religion forever. This four-part docuseries uses never-before-seen footage and first-person accounts to explore the infamous UFO cult that shocked the nation with their out-of-this-world beliefs.</p>1.616784e+09https://api.tvmaze.com/episodes/2005096
1261974913https://www.tvmaze.com/episodes/1974913/heavens-gate-the-cult-of-cults-1x04-the-exitThe Exit1.04.0regular2020-12-03nan2020-12-03T17:00:00+00:0052.0Nonenan52071https://www.tvmaze.com/shows/52071/heavens-gate-the-cult-of-cultsHeaven's Gate: The Cult of CultsDocumentaryEnglish[]EndedNaN51.02020-12-032020-12-03https://www.hbomax.com/heavens-gate47.0nan<p><b>Heaven's Gate: The Cult of Cults</b> is a thorough examination of the infamous UFO cult through the eyes of its former members and loved ones. What started in 1975 with the disappearance of 20 people from a small town in Oregon, ended in 1997 with the largest suicide on US soil and changed the face of modern New Age religion forever. This four-part docuseries uses never-before-seen footage and first-person accounts to explore the infamous UFO cult that shocked the nation with their out-of-this-world beliefs.</p>1.616784e+09https://api.tvmaze.com/episodes/2005098
1272236491https://www.tvmaze.com/episodes/2236491/notruf-hafenkante-15x10-im-rauschIm Rausch15.010.0regular2020-12-0319:252020-12-03T18:25:00+00:0045.0Nonenan17046https://www.tvmaze.com/shows/17046/notruf-hafenkanteNotruf HafenkanteScriptedGerman['Drama', 'Crime']Running45.050.02007-01-04nanhttps://www.zdf.de/serien/notruf-hafenkante4.0nannan1.645352e+09https://api.tvmaze.com/episodes/2005099
1281960030https://www.tvmaze.com/episodes/1960030/goede-tijden-slechte-tijden-31x56-aflevering-6311Aflevering 631131.056.0regular2020-12-0320:002020-12-03T19:00:00+00:0023.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/285/712960.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/285/712960.jpg'}nan2504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch['Drama', 'Romance']Running23.025.01990-10-01nanhttp://gtst.nl/#!/77.0nannan1.651839e+09https://api.tvmaze.com/episodes/2005100
1291976645https://www.tvmaze.com/episodes/1976645/wwe-nxt-uk-2020-12-03-episode-49Episode 492020.049.0regular2020-12-0315:002020-12-03T20:00:00+00:0060.0Nonenan39053https://www.tvmaze.com/shows/39053/wwe-nxt-ukWWE NXT UKSportsEnglish[]Running60.060.02018-10-17nannan84.0nan<p>The one-hour episodes will feature the biggest names from NXT UK, including Pete Dunne, Mark Andrews, Rhea Ripley, Toni Storm, Tyler Bate, Trent Seven and Wolfgang. Joining the NXT UK broadcasting team as backstage interviewer is British broadcasting personality Radzi Chinyanganya, best known for hosting ITV game show "Cannonball," and in his ongoing role as a presenter of the world's longest-running children's TV show, the BBC's "Blue Peter." Calling the action are commentators Nigel McGuinness and Vic Joseph, joined by ring announcer Andy Shepherd and NXT UK General Manager, the legendary Johnny Saint.</p>1.652005e+09https://api.tvmaze.com/episodes/2005101